AI & ML Applications in Reservoir Engineering
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This workshop examines how artificial intelligence and machine learning are reshaping reservoir engineering by enhancing prediction accuracy, streamlining workflows, and enabling data-driven decision-making. Participants will explore practical applications that improve reservoir modeling, production forecasting, and operational efficiency.
Workshop Objectives
• Understand the role of AI and ML in modern reservoir engineering.
• Learn techniques for applying predictive models to reservoir performance.
• Explore case-based applications in production optimization and risk reduction.
• Identify best practices for integrating AI/ML into reservoir workflows.
About the Presenter
The workshop will be conducted by an experienced professional in reservoir engineering, digital transformation, and data analytics. Combining technical depth with applied industry knowledge, the presenter offers practical guidance on leveraging AI and ML to drive efficiency and value in oil and gas operations.
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Machine Learning for Drilling Engineering with Python
Drilling generates huge amounts of data — but most of it sits unused. This hands-on workshop shows you how to turn that data into better decisions using Python and machine learning.Over the sessions, you'll work with real drilling datasets to build models that predict problems before they happen — stuck pipe, ROP optimization, bit wear, formation changes, and more. No heavy math theory. You write code, run it on actual data, and see the results.By the end, you'll have working Python scripts you can adapt to your own field data, plus a clear understanding of where ML adds value in drilling and where it doesn't.Built for drilling engineers, not data scientists. If you can read a drilling report, you can follow this course.